Monitoring Scale Up

A Review of the Guide to Monitoring Scale Up of Health Practices and Interventions by Bridgit Adamou

A friend and former colleague of mine at MEASURE Evaluation has put together an excellent resource of M&E of scale up efforts. This fills a huge gap in the currently available resources on scale up, and addresses and often overlooked fact: many interventions will work as a small pilot; but working at scale, within the health system is an entirely different challenge and needs to be measured as such.

As the process of organized scale up is generally challenging, monitoring can be one way to nurture the process, as H. James Harrington says;

“Measurement is the first step that leads to control and eventually to improvement. If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it” (page 33 of the guide)

The monitoring content is presented in a way that is accessible and useful for a program manager. This ensures monitoring of scale up is a tool for management and quality improvement (as James Harrington suggests), not an academic exercise.

From page 34 of the guide: Monitoring the scale up feedback mechanism is an ongoing process

Other available scale-up resources focus on diffusion and garnering commitment from key stakeholders for scale, and are less concerned with monitoring or evidence. However, M&E is central to scale up in a number of ways. First of all strong M&E at the pilot stage tells us if a project is successful enough to warrant scale up, and what components should be taken to scale and what components should be dropped. The M&E framework and results of the pilot will also help define the innovation and its key components (which ones work, which ones are essential, which ones can be dropped). Only by clearly defining the innovation is scale up or replication possible.

Most of the scale up resources I have seen (available here) use criteria to judge whether a project is ready to be taken to scale from Everett Rogers’ theory of the Diffusion of Innovation. The criteria are; Credible, Observable, Replicable, Relevent, Compatible and Trialable (making the annoying acronym “CORRECT”). However, this resource simplifies it all for us somewhat – giving us new criteria: Clarity, Available Evidence, Integration, Resources and Commitment. I think this is a bold improvement on CORRECT; it is simpler and easier to communicate; and gives proper weight to evidence (I say bold because I always pause before moving on from a well established theory). Using these new criteria, the guide also includes a helpful decision-aid flow chart (see page 9). I say, thank you Bridgit!